What is it about?
The existing data integration systems aim at integrating either incomplete or uncertain data without identifying the different types of each nature of the information. This paper presentes an intelligent data integration approach, proving cooperative answers that best meet the user requirements. To examine the efficiency and effectiveness of our proposed approach, we have developed the fuzzy mediator system and performed extensive experiments. The results prove that the approach improves data integration performance when the incompleteness and uncertainty problems are available independently or simultaneously.
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Why is it important?
The uncertain and incomplete information are two existing information’s natures together in the data source: Dealing with data uncertainty by removing records with uncertain information leads to incomplete query results. In contrast, the incomplete information in the data source allows us to insert inaccurate or uncertain information for completing the data lacking. The proposed approach provides intelligent data integration, enabling efficient generation of cooperative answers from similar ones, retrieved by mediator system.
Perspectives
The integration of incomplete and uncertain databases has become an intrinsic property in many application domains, such as transportation planning, weather information, e-business, bioinformatics field, etc. While the flexible mediator system is generic for many application domains, we focus on the food safety domain. The use of the flexible mediator system in microbiology laboratories and industries provides reliable and efficient management of such datasets, taking into account the conditions of growth of microorganisms in food. I hope you find this article thought-provoking.
Aicha Aggoune
University of 8th May 1945, Guelma, Algeria
Read the Original
This page is a summary of: Intelligent data integration from heterogeneous relational databases containing incomplete and uncertain information, Intelligent Data Analysis, January 2022, IOS Press,
DOI: 10.3233/ida-205535.
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